code: def __word_proposal_distribution(self, word_id, topic):
      wt_beta = (
          self.__model.word_topic_value(word_id, topic)
          + self.__model.beta()
      )
      t_sum_beta_sum = (
          self.__model.topic_sum_value(topic) + self.__model.beta_sum()
      )
      return wt_beta / t_sum_beta_sum
  
imports: import numpy
  from tqdm import tqdm
  from paddlehub.common.logger import logger
  from lda_news.document import LDADoc, SLDADoc, Token, Sentence
  from lda_news.vose_alias import VoseAlias
  from lda_news.util import rand, rand_k
label_desc: Use image node_id 9 for calling the MHSampler obj's underlying member method code with example usage: obj.__word_proposal_distribution(word_id, topic) and returns: unknown